This research aims to propose a new deep learning model for more effective semantic attention in language tasks.
Developed Roken, a recurrent deep learning model.
Focused on implicit learning techniques.
Applied the model to next-token and sequence-to-sequence learning tasks.
Roken improves semantic attention efficiency.
Showed faster performance in language predictions.
Enhanced accuracy in sequence-to-sequence tasks.
Abstract
Roken, a fast implicit recurrent deep learning model of semantic attention is proposed for the purposes of large language model next-token and sequence-to-sequence learning.